Senior Machine Learning Engineer

Senior Machine Learning Engineer (Search, Recommendations & Conversational AI)

Location:

Remote
Role Type:  Senior IC (P3+)
Team:  Discovery – Search, Recommendations & AI Experiences
Urgency:  Immediate (pre–IPL launch milestones)

About the Role
We are building next-generation  conversational search ,  personalized recommendations , and  AI-driven discovery  for one of India’s largest entertainment ecosystems. This role is for a hands-on ML Engineer who can design, train, and product ionize models powering search relevance, retrieval, personalization, and LLM-based conversational experiences at massive scale.
You will work closely with backend, platform, and catalog enrichment teams to deliver high-quality ML components under tight performance and latency constraints.

Key Responsibilities
Build and improve  search ranking ,  retrieval , and  query understanding  models.
Develop ML components for  Conversational Search :
Multi-turn context handling
Query intent detection and classification
Retrieval-augmented generation (RAG) pipelines
Reasoning workflows (ReAct, static + dynamic agent flows)
Design and optimize  embedding models , vector stores, and similarity search systems.
Build  personalized ranking  and recommendation models using deep learning.
Work on  large-scale ML systems  optimized for:
Low latency
High throughput
Cost-efficient inference
Implement ML pipeline best practices (versioning, monitoring, A/B testing, observability).
Collaborate with platform teams to integrate ML services across search, recommendations, and conversational agents.
Develop caching strategies (prompt cache, vector cache, similarity caching) to hit strict SLA targets.
Contribute to long-term roadmap: foundational retrieval models, multi-objective optimization, user lifecycle modeling.

Required Qualifications
4–10 years of experience in  Machine Learning / Applied ML engineering .
Strong foundations in ML, deep learning, Transformers, and neural retrieval.
Hands-on experience with:
Search systems (retrieval + ranking)
Recommendation models
Embedding models & vector databases
Tensor Flow / Py Torch
Proven experience building  production-grade ML systems  iliarity with LLMs, RAG architectures, prompt engineering, and agent workflows.
Strong coding skills (Python) and experience with modern ML stack (Tensor Flow, PyTorch, Faiss/ScaNN, Triton, etc.).
Ability to work closely with backend teams to deploy models in distributed systems.
Excellent problem-solving skills and comfort working on ambiguous, high-impact problems.

Preferred Qualifications

Experience with  conversational AI , chat-based retrieval, or multi-turn dialog modeling.
Experience in  media, streaming, sports data  or large catalog discovery.
Knowledge of micro-drama, short-video personalization, or multi-objective recommendation systems.
Strong understanding of scalability patterns: batching, async orchestration, caching layers.

Why Join
Work on  flagship launches  (World Cup → IPL) impacting hundreds of millions of users.
Solve some of the most challenging problems in search, discovery, and conversational AI laborate with a world-class team building foundational discovery platforms for India’s largest digital ecosystem.